Today, probabilistic mathematical and AI techniques have come to assist neuroscientists in analyzing the brain functionality. This includes deep learning (DL), reinforcement learning (RL), and generative adversarial networks (GANs) [1]}. For instance, in [2]} the neural mechanisms have been studied via probabilistic inference methods.
The brain's structural and functional systems are seen to possess features of complex networks [3]}. It is also shown that neurons as agents, can understand their environment partially, make a decision, and control their internal organs [4]}.
Moreover, Yamins et al. use deep hierarchical neural networks to delve into computational sensory systems models, especially the sensory cortex and visual cortex [5]}.
